Sharif Digital Repository

Artificial neural networks were used to predict the oxidation peaks potentials of 7 monosaccharides under linear sweep voltammetry regime. Two sets of descriptors, one based on molecular properties calculated through DFT and another based on simple geometric distributions of hydroxyl groups and asymmetric carbon atoms along molecular chains, were employed to introduce the molecules to networks. Relatively, simple networks of (3,3,1) and (3,3,3,1) structures with the number of epochs not exceeding 15 through training process were capable of correctly predicting the peaks positions with R values in the range of 0.97-0.99. © 2008 Elsevier Ltd. All rights reserved  

A carbon-paste electrode (CPE) modified with iron(II) phthalocyanine was used for the sensitive voltammetric determination of epinephrine (EN). The electrochemical response characteristics of the modified electrode toward EN, ascorbic acid (AA) and uric acid (UA) were investigated by cyclic and differential pulse voltammetry (CV and DPV). The results show an efficient catalytic activity of the electrode for the electro-oxidation of EN, which leads to improvement of reversibility of the electrode response and lowering its overpotential by more than 100 mV. The effect of pH and potential sweep rate on the mechanism of the electrode process was investigated. The modified electrode exhibits an...